Optimal sensing-order in cognitive radio networks with cooperative centralized sensing

This paper investigates the optimal sensing-order problem in multi-user, multi-channel cognitive radio networks in which channel sensing and access decisions are made sequentially by a central coordinator according to a central sensing-order. Estimates of the primary-free probabilities of the different channels are assumed to be known. Cognitive throughput, which is the sum of expected throughputs of all cognitive users (CUs), is used as the reward function. When the CUs do not use rateadaptation, we show that the optimal central sensing-order is a simple ordering of the channels based on their primary-free probabilities. When the CUs use rate-adaptation, we describe the procedure for mathematically formulating the reward function. In general, a computationally expensive brute force search can be used to find the optimal central sensing-order. We also consider a couple of simple heuristic sensing-orders and compare their performance with that of the optimal sensing-order through simulations.